Clustering: Difference between revisions
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Some of the commonly used clustering algorithms are<ref name="pythonistaplanet">[https://pythonistaplanet.com/applications-of-unsupervised-learning/ Real World Applications of Unsupervised Learning]pythonistaplanet.com</ref>: | Some of the commonly used clustering algorithms are<ref name="pythonistaplanet">[https://pythonistaplanet.com/applications-of-unsupervised-learning/ Real World Applications of Unsupervised Learning]pythonistaplanet.com</ref>: | ||
* [[Partitioned-baseed clustering]]<ref name="MLPython"/>: | * [[Partitioned-baseed clustering]]<ref name="MLPython"/>: | ||
** [[K-means clustering|K-means]]: | |||
** [[K-median]]: | |||
** [[Fuzzy c-means]]: | |||
* [[Hierarchical clustering]]<ref name="MLPython"/>: | * [[Hierarchical clustering]]<ref name="MLPython"/>: | ||
** [[Agglomerative clustering]]: | |||
** [[Divisive clustering]]: | |||
* [[Density-based clustering]]<ref name="MLPython"/>: | * [[Density-based clustering]]<ref name="MLPython"/>: | ||
** [[DBSCAN]]: | |||
=== others === | |||
* [[Expectation maximization]]: | |||
* [[Hierarchical cluster analysis]] (HCA): | |||
== Applications == | == Applications == | ||
Revision as of 22:05, 31 March 2020
Clustering is an unsupervised learning technique. It is used for grouping data points, or objects that are somehow similar. Clustering means finding clusters in a dataset, unsupervised.[1]
Types pof clustering
Some divide clustering into two subgroups[2]:
- Hard clustering: Each data point either belongs to a cluster completely or not.
- Soft clustering: A probability or likelihood is assigned for putting data points into separate clusters.
Clustering vs classification
Algorithms
Some of the commonly used clustering algorithms are[3]:
others
Applications
References
References
- ↑ 1.0 1.1 1.2 1.3 Intro to ClusteringCoursera
- ↑ An Introduction to Clustering and different methods of clusteringanalyticsvidhya.com
- ↑ Real World Applications of Unsupervised Learningpythonistaplanet.com